Can artificial intelligence technology improve green total factor efficiency in energy utilisation? Empirical evidence from 282 cities in China

被引:0
|
作者
Liu, Yingji [1 ]
Guo, Ju [2 ]
Shen, Fangbing [1 ]
Song, Yuegang [1 ]
机构
[1] Henan Normal Univ, Sch Business, Xinxiang, Peoples R China
[2] Henan Normal Univ, Sch Tourism, Xinxiang, Peoples R China
关键词
Artificial intelligence; Green total factor efficiency in energy utilization; Dual carbon goal; Spatial spillover;
D O I
10.1007/s10644-025-09862-7
中图分类号
F [经济];
学科分类号
02 ;
摘要
This study empirically examines the effects and mechanisms of AI on green total factor efficiency in energy utilization (GTFEEU) using panel data covering 282 Chinese prefecture-level cities from 2006 to 2021. First, the findings demonstrate that artificial intelligence (AI) can considerably improve GTFEEU. Second, AI enhances GTFEEU through mechanisms of industrial structure upgrading, financial development, and government innovation preference. Third, AI application level is the key determinant of overall GTFEEU, with no significant difference in its impact between resource-based and non-resource-based cities. Furthermore, the effect of AI on improving GTFEEU is more pronounced in large cities than in medium-sized and small cities. Fourth, significant spatial autocorrelation is evident between AI and GTFEEU, and the spatial spillover effect is primarily short-term. This study provides valuable insights for policymakers on the effects and mechanisms of developing AI technology for GTFEEU improvement.
引用
收藏
页数:34
相关论文
共 42 条
  • [31] Artificial intelligence, resource reallocation, and corporate innovation efficiency: Evidence from China's listed companies
    Li, Chengming
    Xu, Yang
    Zheng, Hao
    Wang, Zeyu
    Han, Haiting
    Zeng, Liangen
    RESOURCES POLICY, 2023, 81
  • [32] Non-Linear Impacts and Spatial Spillover of Digital Finance on Green Total Factor Productivity: An Empirical Study of Smart Cities in China
    Yu, Ying
    Zhang, Qian
    Song, Fan
    SUSTAINABILITY, 2023, 15 (12)
  • [33] Artificial Intelligence Drives the Coordinated Development of Green Finance and the Real Economy: Empirical Evidence from Chinese Provincial Level
    Peng, Gangdong
    Han, Minchun
    Yuan, Hankun
    JOURNAL OF THE KNOWLEDGE ECONOMY, 2023, 15 (3) : 10257 - 10295
  • [34] Artificial intelligence-driven transformations in low-carbon energy structure: Evidence from China
    Tao, Weiliang
    Weng, Shimei
    Chen, Xueli
    Alhussan, Fawaz Baddar
    Song, Malin
    ENERGY ECONOMICS, 2024, 136
  • [35] Does the adoption of artificial intelligence by audit firms and their clients affect audit quality and efficiency? Evidence from China
    Rahman, Md Jahidur
    Zhu, Hongtao
    Yue, Li
    MANAGERIAL AUDITING JOURNAL, 2024, 39 (06) : 668 - 699
  • [36] How Artificial Intelligence-Assisted Colour Lighting Can Improve Learning: Evidence from Recent Classrooms Studies
    Quiles-Rodriguez, Jose
    Palau, Ramon
    Mateo-Sanz, Josep M.
    APPLIED SCIENCES-BASEL, 2025, 15 (07):
  • [37] Digital Economy Development and Green Economic Efficiency: Evidence from Province-Level Empirical Data in China
    Kong, Lingzhang
    Li, Jinye
    SUSTAINABILITY, 2023, 15 (01)
  • [38] Research on the impact of the national ecological demonstration zone on green total factor productivity: Evidence from China
    Yuan, Chunlai
    Shang, Meiling
    Han, Zhaojie
    Wang, Jiating
    JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2024, 356
  • [39] The spatial spillover effect of China's pollutants emission trading pilot scheme on green efficiency: evidence from 285 China's cities
    Wang, Kaifeng
    Zhong, Chunping
    Chen, Lifeng
    Zeng, Yunmin
    ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY, 2023, 25 (08) : 8137 - 8163
  • [40] The spatial spillover effect of China’s pollutants emission trading pilot scheme on green efficiency: evidence from 285 China’s cities
    Kaifeng Wang
    Chunping Zhong
    Lifeng Chen
    Yunmin Zeng
    Environment, Development and Sustainability, 2023, 25 : 8137 - 8163